PID Controller Design for MIMO Processes Using Improved Particle Swarm Optimization

被引:25
作者
Chang, Wei-Der [1 ]
Chen, Chih-Yung [1 ]
机构
[1] Shu Te Univ, Dept Comp & Commun, Kaohsiung 824, Taiwan
关键词
Improved particle swarm optimization (IPSO); MIMO; PID controller design; Subpopulation; SYSTEMS;
D O I
10.1007/s00034-013-9710-4
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper aims at the PID control system design for multivariable input and multivariable output (MIMO) processes. An improved version of a particle swarm optimization (PSO) algorithm is utilized to design PID control gains in MIMO control systems. In addition to the individual best and the global best particles, the velocity updating formula of the developed algorithm includes a new factor, the best particle of each sub-population, to enhance the search capacity. Based on the improved particle swarm optimization (IPSO), a complete design strategy is proposed for MIMO PID control systems. All control gains will be evolved to the optimal values by minimizing the system performance criterion. To show the efficiency of the proposed design method, a multivariable chemical process system with two inputs and two outputs is illustrated. Some experiment results, including different algorithm parameter settings and comparisons with other methods, are given. Numerical simulations indicate that the proposed method is superior to other optimal methods.
引用
收藏
页码:1473 / 1490
页数:18
相关论文
共 23 条
[1]   Multivariable PID control with set-point weighting via BMI optimisation [J].
Bianchi, Fernando D. ;
Mantz, Ricardo J. ;
Christiansen, Carlos F. .
AUTOMATICA, 2008, 44 (02) :472-478
[2]   A multi-crossover genetic approach to multivariable PID controllers tuning [J].
Chang, Wei-Der .
EXPERT SYSTEMS WITH APPLICATIONS, 2007, 33 (03) :620-626
[3]   PID controller design of nonlinear systems using an improved particle swarm optimization approach [J].
Chang, Wei-Der ;
Shih, Shun-Peng .
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2010, 15 (11) :3632-3639
[4]   Digital Modeling and PID Controller Design for MIMO Analog Systems with Multiple Delays in States, Inputs and Outputs [J].
Chang, Y. P. ;
Shieh, L. S. ;
Liu, C. R. ;
Cofie, P. .
CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2009, 28 (01) :111-145
[5]   A tuning strategy for multivariable PI and PID controllers using differential evolution combined with chaotic Zaslavskii map [J].
Coelho, Leandro dos Santos ;
Pessoa, Marcelo Wicthoff .
EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (11) :13694-13701
[6]   Model order formulation of a multivariable discrete system using a modified particle swarm optimization approach [J].
Deepa, S. N. ;
Sugumaran, G. .
SWARM AND EVOLUTIONARY COMPUTATION, 2011, 1 (04) :204-212
[7]   Evolutionary algorithms based design of multivariable PID controller [J].
Iruthayarajan, M. Willjuice ;
Baskar, S. .
EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (05) :9159-9167
[8]  
Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
[9]  
Kuo BC, 1995, Automatic Control Systems
[10]   A novel particle swarm optimization algorithm based on particle migration [J].
Ma Gang ;
Zhou Wei ;
Chang Xiaolin .
APPLIED MATHEMATICS AND COMPUTATION, 2012, 218 (11) :6620-6626